GB2513472A - Resolving similar entities from a database - Google Patents

Resolving similar entities from a database Download PDF

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Publication number
GB2513472A
GB2513472A GB1404499.4A GB201404499A GB2513472A GB 2513472 A GB2513472 A GB 2513472A GB 201404499 A GB201404499 A GB 201404499A GB 2513472 A GB2513472 A GB 2513472A
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Prior art keywords
records
merchant
record set
record
transaction
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GB201404499D0 (en
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Daniel Erenrich
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Palantir Technologies Inc
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Palantir Technologies Inc
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Priority to US13/827,491 priority Critical patent/US10140664B2/en
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Publication of GB2513472A publication Critical patent/GB2513472A/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/10Tax strategies
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22Indexing; Data structures therefor; Storage structures
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35Clustering; Classification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35Clustering; Classification
    • G06F16/355Class or cluster creation or modification
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02Banking, e.g. interest calculation, credit approval, mortgages, home banking or on-line banking

Abstract

A plurality of record sets where each record set includes one or more common attribute values is retrieved from the database. An exemplar record set associated with a first entity record set is selected and a classifier 255 determines a probability that the record set includes records associated with the first entity. The determined probability is then compared to a threshold to assess whether the record set includes records associated with the first entity. The classifier is preferably a random forest classifier and the record sets are preferably financial transaction records processed for a financial institution by a merchant.

Description

Resolving Similar Entities From A Database

Field of the Invention

Embodiments of the present invention generally relate to data analysis and, more specifically, to resolving similar entities from a database.

Description of the Related Art

Obtaining relevant information from large databases can be relatively straightforward in some situations. Particularly, when the data records in a database are well-io structured and it is desired to obtain information in records having a particular value or character string in a particular field, those records can be isolated using filtering functions of database interfacing software. Using combinations of filtering functions, more sophistication can be provided to the way in which records are identified for isolation. The isolated records may then be aggregated so as to provide a report i including all the records that together constitute the desired information.

However, in order to denote database records having commonality, such filtering functions rely on identical attributes across those database records. Tn the real worM, database records may not have identical attributes across those records despite those records being related, or may have identical attributes in a relatively small number of fields (or parts of fields) such that filtering functions are unable to provide isolation of the desired database records from other database records. For example, such problems can occur when a database has database records originating from a number of different sources. The isolation of related database records from other database records is a technical problem that becomes worse as the database becomes larger (e.g., a database having billions of database records), in terms of the number of records present. With the sizes of databases in the real world increasing as time progresses, this problem is expected to worsen over time.

Embodiments of the invention address the problem of identifying related database records that may have not have useful identical attributes whilst excluding unrelated database records, and in particular solve the problem of identifying database records that relate to a common entity but which may have no identical attributes.

3 A first aspect of the invention provides a method for identifying related records from a database storing records for multiple entities as daimed in claim 1.

A second aspect of the invention provides a computer system as daimed in claim 12.

Optional features are listed in the dependent claims or are recited in the detailed

description embodiments.

One advantage of the disclosed technique is that two record sets in a database of records that have no identical attributes, but belong to the same common entity, may be linked to the common entity. Therefore, resolutions that would be missed with jo string comparisons alone are made and incorrect resolutions based only on similar strings are avoided, which improves the resohition precision. Another advantage of the disclosed technique is that it reduces the number of mistaken aggregates resulting from records having similar identifiers despite being associated with different entities. By reducing the number of mistaken aggregates, an aggregated report of record sets thus provided occupies less memory than a corresponding aggregated report produced by filtering functions.

Brief Description of the Drawings

So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.

Figure 1 is a block diagram illustrating a computer system configured to implement one or more aspects of the present invention.

Figure 2 is a block diagram of the flow of data in through the appfication server.

Figure 3 illustrates a method for training the classifier, according to one embodiment.

Figure 4 illustrates a method of resolving merchant ID to a merchant, according to one embodiment.

Figure 5 illustrates an example of a computing environment, according to one embodiment.

Detailed Description

Embodiments of the invention may be used to aggregate certain records that are resolved to a common entity, but might not otherwise be grouped with one another.

Assuming a database identifies records from each distinct account of an entity by a distinct ID attribute, then the distinct ID attributes may not be matched correctly to link the records of the accounts with the entity.. In one embodiment, a system jo combines records into ID sets based upon identical IDs, so each TD set contains afl of the records with a particular ID. As this example illustrates, a single entity maybe represented by multiple IDs. To evaluate the full set of records for a single entity each collection of records (the ID sets) associated with the single entity need to be merged together.

For example, embodiments of the invention may be used to aggregate certain financial transaction records that are resolved to a common entity, but might not otherwise be grouped with one another. Assuming a transaction database of a financial institution identifies transaction records from each distinct merchant account of a company by a distinct merchant ID attribute, then the distinct merchant IDs attributes may not be matched correctly to link the transaction records of the accounts with the company. As another example, different franchisees of common franchisor will have spate merchant accounts, making it difficult to aggregate the transaction records associated with all franchisees of the franchisor from the transaction records alone. In one embodiment, a financial analysis system combines transaction records into merchant ID sets based upon identical merchant IDs, so each merchant ID set contains all of the transaction records with a particular merchant ID. As this example illustrates, a single company may be represented by multiple merchant IDs. To evaluate the full set of transaction rccords for a singic cntity (company) cach collcction of financial transaction rccords (the merchant ID sets) associated with the single entity need to be merged together.

Background art for handling transaction records will now be described.

Financial institutions store transactional data for analysis. A financial institution generates transactional data from credit and debit card purchases at companies that have a merchant account with the financial institution. The merchant account may be used to processes individua' credit or debit card purchases. in turn, each such purchase is stored as a transaction record in a transaction database. A transaction record associated with a particular merchant account oftentimes includes a merchant TD attribute that links the transaction record to the merchant account. A merchant TD may be any data type, induding a number, a string, or some combination thereof. The financial institution may then ana'yze the transaction records from one or more merchant accounts. For example, an analysis may involve aggregating the transaction records of a merchant account or particular merchant accounts. The analysis may then compare the performance of the merchant account to that of competing merchant o accounts in the same geographic area.

Although the financial institution stores the transaction records in a database of transactions, certain ana'ysis may require the data to be organized in ways that are not part of the transaction records in the database. These databases contain sets of transaction records that an analysis should group together, even though there is no single attribute vahie that relates the transaction records. For example, if a flnancia institution configures a database of transactions with a merchant TD attribute that Unks each transaction record to a merchant account, then an analysis would easily aggregate transaction records with the same merchant ID together. However, a sing'e company may have multiple merchant accounts with a financial institution. If the financial institution provides distinct merchant IDs for every merchant account, even when multiple merchant accounts belong to a singk company, then it is difficult to aggregate transaction records together from the multip'e merchant accounts of that company.

For instance, a franchise company may have distinct merchant accounts with distinct merchant IDs for each franchisee location, in such a case, an analysis could not aggregate the transaction records of the franchise company together based on identical merchant IDs alone. Instead, an analysis can use similarities between the merchant ID attribute values to aggregate the transaction records of the franchise company together.

Existing techniques rely upon simple tests, such as string comparisons between an attribute in a database of transaction records to detect similarities between groups of transaction records. Transaction records including attribute strings that meet a measure of similarity are then aggregated together for analysis. These techniques may work as tong as the attribute contains strings that are identical or similar for groups of transaction records that should be aggregated together and strings that are distinct for groups of transaction records that should not be aggregated together.

However, such identifiers are not always (or even usually) available. For example, different merchant TDs for the merchant accounts of a single company may prevent an analysis system from aggregating the transaction records of the company together.

Furthermore, transaction records may contain similar identifiers that an analysis system may base aggregations upon, even if the transaction records should not be aggregated together. For example, two different companies may have merchant accounts with similar merchant IDs, which an analysis system could mistakenly match to one company. The analysis system may then mistakenly aggregate the transaction jo records of the two companies together.

As the foregoing illustrates, there remains a need for more effective techniques evaluating financial transaction records.

Tn one embodiment, the analysis system aggregates transaction records from a large collection of merchant TD sets. This aggregation may include ca'culating the average transaction size, the transaction size standard deviation, or the average amount that an individual has spent. The analysis system uses the aggregates to train a classifier. Once trained, the analysis system produces a confidence score of whethertwo merchant ID sets belong to a company, based upon the aggregates from the pair of merchant TD sets.

To associate the merchant 1D sets to the company, the analysis system receives a selection of an exemplar merchant tD set that should be associated with the company and best represents the characteristics of the company. The analysis system compares the exemplar merchant ID set with other merchant ID sets to determine a confidence score. The confidence score represents the likelihood that the exemplary merchant TD set and the other merchant TD set is associated with the company. The analysis system associates every merchant ID set having a confidence scores above a threshold, when compared with the exemplar, to the company. Doing so results in a collection of financial transaction rccords that prcsumably all belong to onc company, dcspitc thc fact that many of such records may include different merchant TDs.

Tn the following description, numerous specific details are set forth to provide a more thorough understanding of the present invention. However, it wifl be apparent that the present invention maybe practiced without one or more of these specific details.

Figure 1 is a block diagram illustrating an example data analysis system 100, according to one embodiment of the present invention. As shown, the data analysis system 100 includes an application server 140 running on a server computing system 130, a client running on a client computer system 110, and at least one transaction database 160.

Further, the client 120, application server 140, and transaction database 160 may communicate over a network 180.

The client 120 represents one or more software applications configured to present data and translate user inputs into requests for data analyses by the application server 140.

jo Tn this embodiment, the client 120 connects to the application server 140. However, several clients 120 may execute on the client computer 110 or several clients 120 on several client computers 110 may interact with the application server 140. Tn one embodiment, the client 120 may be a browser accessing a web service.

Alternatively, the cfient 120 may run on the same server computing system 130 as the application server 140. In any event, a user would interact with the data analysis system 100 through the client 120.

The application serrer 140 is configured to include a merchant resolution tool 150 and an analysis engine 155. The merchant resolution tool 150 links matching merchant IDs to a company. The merchant resolution tool 150 reads data from the transaction database 160. The merchant resolution tool 150 may store resolution data on the sewer computer 130 or on the transaction database 160.

The analysis engine 155 uses the resolution data from the merchant resolution tool 150 to analyze data retrieved from the transaction database i6o. The analysis engine 155 aggregates and compares the transaction records from the transaction database i6o to provide insights about a particular company. For instance, a financial institution may dcsign a data analysis to evaluate thc seasonal spending trends for a franchise company. However, each franchisee of the franchise company may have a distinct merchant account with the financial institution. The financial institution stores the transaction records from the merchant accounts with distinct merchant TDs that associate a transaction record with a merchant account. To evaluate the full set of transaction records for the franchise company the analysis engine 155 needs to merge each collection of financial transaction records from each franchisee together.

Therefore, the analysis engine 155 uses the resolution data from the merchant resolution tool 150 to merge the financial transaction records from each franchisee together into a full set of transaction records for the franchise company in order to evaluate the seasonal spending trends for the franchise company.

In this embodiment, the transaction database 160 stores data records of financial transactions associated with a financial institntion. For example, the transaction database may include data records for a large number of merchant accounts processing credit and debit card transaction. In such a case, each record would include data attributes for the amount spent, the transaction date and time, the address of the o merchant, and a merchant ID to associate the record with a particular merchant account.

The transaction database i6o may be a Relational Database Management System (RDBMS) that stores the transaction data as rows in relational tables. Alternatively, the transaction database 160 maybe stored on the same server computing system 130 as the application server 140. The data records of a financial institution Figure 2 illustrates a flow of data from the transaction database 160 through the merchant resolution tool 150, according to one embodiment of the present invention.

As shown, the transaction database i6o includes merchant ID sets 210. Each merchant ID set 210 includes transaction records 215 with the same merchant ID, such as credit and debit card transactions processed for a single merchant account at a financial institution. The merchant resolution tool 150 includes an aggregator 240, candidate aggregates 242, exemplar aggregates 244, training data set 260, and an identity resolver 250. The identi' resolver 250 itself includes a classifier 255 and a resolve list 270.

In one embodiment, the classifier 255 is a random forest classifier. A random forest classificr is a machinc Icarning algorithm that is gcncrally known to bc highly accuratc on large databases that include discrete, continuous, and missing data, as may be the case for financial transaction records 215 in the transaction database i6o. Random forest classifiers include multiple decision trees. The decision trees evaluate features of input data. In the present context, of financial transaction records that are associated with merchant accounts by a merchant id, the evaluated features may include: Word overlap count and frequency of merchant tD attributes * Word-based cosine similarity weighted by per-term inverse docnment freqnency scores of merchant ID attributes * Character-based cosine similarity of merchant ID attributes * Pthcement of word overlap of merchant ID attributes * Identification of the string ".com" * If the merchant ID attribntes includes a store code * Overlap of prefix or suffix digits in the merchant ID attributes * Whether the provided city is numeric * Matching unique merchant category codes * Fractional difference in average ticket amounts * Standard deviations from the average ticket amounts * Fractional difference in magnitude of the ticket amount variances Note, the dassifier 255 may evaluate a variety of other features, depending on the needs of a particular case and data available from the underlying transaction records. Further one of ordinary skill in the art wifl recognize that a random forest classifier is used as a reference example of a classifier and that a variety of other machine learning dassifiers could be used.

To evaluate the variety of features the dassifier 255 grows decision trees based upon the probability that a selected feature should lead to a certain classification. In the present context, the dassifler 255 grows several decision trees based upon different combinations of the features, so that each decision tree classifies a pair of merchant tD sets 210 as matching the same company or not. The output of the classifier 255 is the percentage of decision trees that classify a pair of merchant ID sets 210 as matching the same company.

To prepare for linking merchant IDs to a company, the classifier 255 grows the decision trccs by training on thc training data sct 260. Thc training data sct 260 includcs pairs of merchant ID sets 210 that match the same company and pairs of merchant TD sets 210 that do not match the same company. The pairs of merchant TD sets 210 that match the same company are classified as positive examples in the training data set 260. The pairs of merchant ID sets 210 that do not match the same company are classified as negative examp'es in the training data set 260. As the classifier 255 processes the features of each pair of merchant ID sets 210 as a positive or negative example, the classifier 255 becomes more accurate by refining the probabilities used in the decision trees.

The training data set 260 may also include difficult edge cases, such as pairs of merchant tD sets 210 that do not match, but have similar merchant ID strings. A pair of merchant ID sets 210 with similar merchant ID strings that should not be linked to the same company is an edge case, because oftentimes similar merchant ID strings come from merchant ID sets 210 that should be linked to the same company. Adding such edge cases to the training data set 260 causes the classifier 255 to adjust the Jo probabilities in the decision trees of the classifier 255 to better classify pairs of merchant ID sets 210 with similar merchant TD attributes.

To create a large training data set 260, the merchant resolution tool 150 may generate pairs of randomly selected merchant ID sets 210, which typically provide negative

training examples.

The training data set 260 may include transaction records 215 retrieved from the transaction database 160, may include synthetic transaction records 215, or may include some combination thereof. While a training data set 260 of 4,000 pairs of merchant ID sets 210 has proven to be effective, the actual size of the training data set 260 may be set as a matter of preference.

Once the classifier 255 is trained, the merchant resolution tool 150 may be used to associate merchant IDs from distinct merchant account to a company, so that the analysis engine 155 may run data analyses on full sets of transaction records 215 from all merchant accounts of the company.

The transaction database 160 is configured to include a mechanism for providing transaction rccords 215 with a common mcrchant TD attributc as merchant ID scts 210.

For example, the transaction database 160 may store transaction records 215 with equal merchant ID attributes together in merchant ID sets 210 or the transaction database may store transaction records 215 sequentially by the value of a transaction date attribute. Regardless of the arrangement of the transaction records 215, the merchant resolution tool 150 may retrieve merchant ID sets 210 from the transaction database 160. -10-

After a user selects a merchant 1D set 210 as an exemplar merchant ID set 210(0), other merchant ID sets 210 maybe considered as candidate merchant ID sets 210(1) throngh 21o(M-1). The user selects the exemplar merchant TD set 210(0) as being representative of the characteristics of the company to be resolved. The exemplar merchant ID set may include a large number of transaction records 215. A large number of transaction records 215 may provide aggregates, such as the average transaction size, that are more accurate than merchant ID sets 210 with fewer transaction records 215. Other factors, such as geographic locations, the merchant ID string, or other business heuristics may also guide the selection of the exemplar jo merchant ID set 210(0) from the available merchant ID sets 210.

When linking merchant IDs to a company, the merchant resolution tool 150 retrieves the transaction records 215 of the exemplar merchant ID set 210(0) and the transaction records 215 of a candidate merchant ID set 210(1). The aggregator 240 aggregates the attributes of the transaction records 215 of the exemp'ar merchant TD set 210(0) to produce exemplar aggregates 244. For example, the aggregator 240 calculates the average transaction size, the transaction size standard deviation, or the average amount that an individual has spent. The merchant ID attribute of the exemplar merchant ID set 210(0) is also included with the exemplar aggregates 244. The aggregator 240 also calculates the candidate aggregates 242 from the candidate merchant ID set 210 and includes the merchant ID attribute of the candidate merchant tD set 210(1) with the candidate aggregates 242. Note that the aggregator 240 may calculate additional aggregate values, according to numerous different designs that the tool developer can choose.

After the aggregator 240 determines the aggregate values, the merchant resolution tool passes the exemplar aggregate 244 and the candidate aggregate 242 to an identity resolver 250. The classifier 255 determines the values used as features in the decision trccs from thc data includcd in thc cxcmplar aggrcgatcs 244 and thc candidatc aggregates 242. The dassifier 255 processes the exemplar aggregate 244 and the candidate aggregate 242 to produce a confidence score between zero and one equal to how likely the exemplar merchant TD set 210(0) matches the candidate merchant TD set 210(1) and should therefore be linked to the same company. If the exemplar merchant ID set 210(0) and the candidate merchant 1D set 201(1) receive a score over some threshold, such as 0.70, then the identity resolver 250 stores the merchant ID of the candidate merchant tD set 201(1) in a resolve list 270.

-11 -The merchant resolution tool 150 compares candidate merchant ID sets 210(2) through 210(M-1) with the exemplar merchant TD set 210(0). The identity resolver 250 adds the merchant ID of each candidate merchant ID set 210(1) through 210(M-1) that produces a high confidence score to the resolve list 270. Therefore, the merchant IDs on the resolve list 270 represent the merchant ID sets 210 that belong to the same company as the exemplar merchant ID set 210(0).

The merchant resolution tool 150 stores the resolve list 270 for use by the analysis jo engine 155. Tn turn, the analysis engine 155 may analyze the full collection of transaction records 215 of the company independent of the various merchant TDs included in the transaction records 215 of the company. For example, if the various merchant IDs in a resolve list 270 associate transaction records 215 with multiple merchant accounts from multiple franchisees of a franchise company. Then the analysis engine 155 shoffid merge the transaction records 215 with the merchant TDs in the resolve list 270 to ana'yze the fufi collection of transaction records 215 of the franchise company.

Figure 3 is a flow diagram of method steps for training the classifier 255, according to one embodiment of the present invention. Although the method steps are described in conjunction with the systems of Figures 1-2 and j, persons of ordinaiy skill in the art will understand that any system configuration to perform the method steps, in any order, is within the scope of the invention.

As shown, method 300 beings at step 305, where a merchant resolution tool 150 creates a training data set 260 of positive examples of pairs of merchant ID sets 210 that link to the same company. The merchant resolution tool 150 adds edge cases to the training data set 210. The edge cases include pairs of merchant ID sets 210 that do not match, but have similar merchant ID strings. Thc cdgc cascs may also include pairs of merchant ID sets 210 that have similar aggregate values, but are from different companies, so are actually negative training examples.

In step 310, the merchant resolution tool io adds randomly selected pairs of merchant ID sets 210 to the training data set 260. The randomly selected pairs of merchant ID sets 210 should include a majority of negative training examples.

-12 -In step 315, the merchant resolution tool 150 submits each merchant iD sets 210 in the training data set 260 to the aggregator 240 to generate candidate aggregates 242.

When training the classifier 255, there is no exemplar merchant ID set 210(0), so all merchant ID sets 210 in the training data set 260 are considered candidates merchant ID sets 210(1) through 210(M-1). A user may review these candidate aggregates 242.

In step 320, the user selects pairs of merchant ID sets 210 that should be linked to the same company as positive training examples.

jo In step 325, the user selects pairs of merchant ID sets 210 that link to different companies as negative training examples. These negative training examples include several difficult edge cases. Additionally, the training data set 210 includes a majority of random selections, so the majority of the pairs of merchant ID sets 210 in the training data set 260 are negative training examples.

In step 330, the merchant resolution tool io trains the dassifier 255 with the training data set 260. As described, the classifier 255 is a random forest learning a'gorithm.

After training the classifier 255 with the training data set 260, the classifier 255 may evaluate a pair of merchant ID sets 210 to produce a confidence score, e.g., a value between zero and one. The confidence score equals the percent of decision trees in the random forest algorithm used by the classifier 255 that determine that both merchant ID sets 210 in the pair should be linked to the same company. Therefore, the classifier 255 is able to produce a confidence score that represents whether a pair of merchant ID sets 210 including an exemplar merchant ID set 210(0) and a candidate merchant ID set 210(1) should be linked to the same company.

Figure 4 is a flow diagram of method steps for linking merchant IDs to a company according to onc cmbodimcnt of thc prcscnt invcntion. Although thc mcthod stcps arc described in conj unction with the systems of Figures 1-2 and, persons of ordinary skifl in the art will understand that any system configuration to perform the method steps, in any order, is within the scope of the invention.

As shown, method 400 beings at step 410, where the merchant resolution tool io receives an exemplar merchant ID as the merchant ID attribute for an exemplar merchant tD set 210(0). As described, a user selects the exemplar merchant tD set -13 - 210(0) as being representative of the characteristics of the financial transaction records 215 associated with a company, e.g., the franchisee that best represents a given franchise company. Alternatively, the system may automatically choose an exemplar merchant ID set 210(0) based on user-specified criteria.

In one embodiment, the merchant resolution tool 150 presents an exemplar selection tool to the user. The exemplar selection toot provides assistance in se'ecting an exemplar merchant ID that is representative of a company to be resolved. The exemplar selection tool may accept a search string from the user to identi' merchant Jo TDs that should potentially be linked to the company. The exemplar selection tool may also use some subset of the company name as the search string. Furthermore, the exemplar selection tool may submit the merchant ID sets 210 associated with the identified merchant IDs to the aggregator 240. The aggregator 240 then computes aggregates 242 that assist the user in sekcting the exemplar merchant ID.

Tn step 420, the merchant resolution tool 150 generates exemplar aggregates 244 for the selected exemplar merchant TD set 210(0). After the merchant resolution tool io retrieves the exemplar merchant ID set 210(0) from the transaction database ibo, the aggregator 240 calculates the average transaction size, the transaction size standard deviation, and the average amount that an individual has spent.

In step 430, the merchant resolution tool 150 generates candidate aggregates 242 for a candidate merchant ID set 210(1). The merchant resolution tool 150 identifies a merchant ID set 210(1) through 210(M-1) that has not been compared to the exemplar merchant ID set 210(0), as the candidate merchant ID set 210(1). Once identified, the merchant resolution tool 150 retrieves the candidate merchant ID set 210(1) from the transaction database i6o, and submits the candidate merchant ID set 210(1) to the aggregator 240. The aggregator 240 generates the candidate aggregates 242.

The aggregation and comparison of every possible merchant ID record set 210(1) through 210(M-1) maybe very time consuming, so reducing the number of comparisons is desirable. Tn one embodiment, the merchant resolution tool 242 does not compare every merchant ID record set 210. The merchant resolution tool 242 skips merchant tD record sets 210 that do not meet a certain qualification. Assuming a franchise company only has franchisee locations in the state of California and the transaction records 215 include an attribute for the address at which the transaction occurred, then the merchant resolution todl 242 would skip those merchant ID record sets 210 that do not include transaction records 215 from California. In this case, the merchant resolution tool 242 reduces the number of comparisons by skipping those merchant ID sets 210 that are not from California.

In step 440, the merchant resolution todl 150 determines if the exemplar merchant ID set 210(0) and the candidate merchant ID set 210(1) match one another and therefore should be linked to the same company. The identity resolver 250 submits the exemplar aggregates 244 and the candidate aggregates 242 to the classifier 255. As described, the o classifier 255 produces a confidence score between zero and one equal to the percent of decision trees in the random forest algorithm used by the classifier 255 that determine that both merchant ID sets 210 in the pair should be linked to the same company. If the classifier 255 produces a confidence score under a threshold, then the method 400 proceeds to step 460. If, however, the confidence score is over the thresho'd, then method 400 proceeds to step 450. While a threshold confidence score of 0.70 has proven to be effective, the actual threshold maybe set as a matter of preference.

In step 450, the identity resolver 250 stores the merchant ID attribute of the candidate merchant ID set 201(1) in a resolve list 270.

In one embodiment, the merchant resolution tool 242 merges the exemplar merchant ID set 240(0) and the candidate merchant ID set 240(1) into a combined merchant ID set, which becomes a new larger exemplar merchant ID set 240(0). Then the merchant resolution tool 242 re-generates the exemplar aggregates 244 for the remaining comparisons. In doing so, the new exemplar merchant ID set 240(0) may better represent the company and improve the resolution of the remaining candidate merchant ID sets 240(2) through 240(M-1).

Tn stcp 460, thc mcrchant rcsolution tool 150 dctcrmincs if thcrc arc morc merchant ID sets 210 in the transaction database 160 that have not been compared. If the merchant resolution tool io determines there is another candidate merchant TD set 210(2) to compare, then the method 400 returns to step 430. Once no more candidate merchant ID sets 210 remain to compare, the merchant resolution tool io links merchant ID sets 210 listed in the res6lve list 270 for the company.

-15 -In step 470, the merchant resolution tool 150 links the exemplar merchant ID set 210(0) with the candidate merchant ID sets 210(1) through 210(M-1) listed in the resolve list 270. As described, the resolution of the merchant TD sets may involve storing a list of merchant ID attributes that the analysis engine i can use to identi1z the transaction records 215 of the company. Alternatively, the merchant resolution tool may link the transaction records 215 of the merchant ID sets 210 on the resolve list 270 to the company by populating an attribute of the transaction records 215 with the company name, so that the analysis engine 155 can query the transaction database i6o for the transaction records 215 belonging to the company.

Figure illustrates an example server computing system io running a merchant resolution tool 150, according to one embodiment. As shown, the server computing system 130 includes, a central processing unit (CPU) 550, a network interface 570, a memory 520, and a storage 530, each connected to an interconnect (bus) 540. The server computing system 130 may also include an T/O device interface 560 connecting T/O devices s8o (e.g., keyboard, display and mouse devices) to the computing system 130. Further, in context of this disclosure, the computing elements shown in server computing system 130 may correspond to a physical computing system (e.g., a system in a data centre) or may be a virtual computing instance executing within a computing cloud.

The CPU 550 retrieves and executes programming instructions stored in memory 520 as well as stores and retrieves application data residing in memory 520. The bus 540 is used to transmit programming instructions and application data between the CPU 550, I/O device interface 6o, storage 530, network interface 570, and memory 520. Note that the CPU 550 is included to be representative of a single CPU, multiple CPUs, a single CPU having multiple processing cores, a CPU with an associate memory management unit, and the like. The memory 520 is generally included to be rcprcscntativc of a random acccss mcmory. Thc storagcs3o may bc a disk drivc storagc device. Although shown as a sing'e unit, the storage 530 maybe a combination of fixed and/or removable storage devices, such as fixed disc drives, removable memory cards, or optica' storage, network attached storage NAS), or a storage area-network (SAN).

The communications between the client 120 and the merchant resolution tool io are transmitted over the network 180 via the network interface 570.

Illustratively, the memory o includes a merchant resolution tool 150, exemplar aggregates 244, candidate aggregates 242, and a resolve list 270. The merchant resolution tool io itself includes an aggregator 240 and a classifier 225. The storage 530 includes a training data set s33, which the merchant resolution tool io uses to train the dassifler 225.

The aggregator 240 generates the exemplar aggregates 244 and the candidate aggregates 242 from transaction records 215 retrieved from the transaction database iôo. The merchant resolution tool 150 issues database queries over the network 180 to jo the transaction database 160 via the network interface 570. Once the aggregator 240 generates the exemplar aggregates 244 and candidate aggregates 242, the merchant resolution tool 150 uses the classifier 225 to determine if the merchant IDs sets 240 should be linked to a company.

Although shown in memrny 520, the merchant resolution toot 150, exemplar aggregates 244, candidate aggregates 242, and resolve list 270, may be stored in memory 520, storage 530, or split between memory 520 and storage 530. Likewise, the training data set 533 maybe stored in memory 520, storage 530, or split between memory 520 and storage 530.

In some embodiments, the database repository 160 may be ocated in the storage 530.

In such a case, the database queries and subsequent responses are transmitted over the bus 540. As described, the client 120 may also be located on the server computing system 130, in which case the client 120 would also be stored in memory 520 and the user would utilize the I/O devices 8o to interact with the client 120 through the I/O device interface 6o.

While the foregoing is directed to embodiments of the present invention, other and furthcr cmbodimcnts of the invention may bc dcviscd without departing from thc basic scope thereof. For examp'e, aspects of the present invention maybe imp'emented in hardware or software or in a combination of hardware and software. One embodiment of the invention may be implemented as a program product for use with a computer system. The program(s) of the program product define functions of the embodiments (induding the methods described herein) and can be contained on a variety of computer-readable storage media. Examples of computer-readable storage media include (i) non-writable storage media (e.g., read-only memory devices within a -17-computer, CD-ROM disks readable by a CD-ROM drive, flash memory, ROM chips or any type of solid-state non-v&atile semiconductor memoiy); and (ii) writable storage media (e.g., floppy disks within a diskette drive or hard-disk drive or any type of soUd-state random-access semiconductor memory) on which alterable information is stored.

The invention has been described above with reference to specific embodiments. It will be understood however, that various modifications and changes may be made thereto without departing from the scope of the invention as set forth in the appended claims.

The foregoing description and drawings are, accordingly, to be regarded in an o illustrative rather than a restrictive sense.

Therefore, the scope of the present invention is determined by the claims that follow.

Claims (20)

  1. -i8 -Claims 1. A method for identifying related records from a database storing records for multiple entities, the method comprising: retrieving a plurality of record sets, wherein each record set includes one or more of the records sharing a common attribute value; receiving a selection of or selecting an exemplar record set, wherein the exemplar record set comprises a plurality of the records associated with a first entity; for each of the plurality of record sets: determining a probability that the record set stores records associated with the first entity by passing a record set and the exemplar record set to a classifier, wherein the classifier is configured to determine the probability that the record set stores records associated with the first entity, and upon determining the probability exceeds a threshold, resolving the record set as storing records associated with the first entity.
  2. 2. The method of daim 1, wherein the classifier is a random forest classifier.
  3. 3. The method of claim 1 or claim 2, further comprising, training the classifier using a plurality of training examples, the training examples comprising: one or more first pairs of record sets, wherein each first pair represent a common entity; and one or more second pairs of record sets, wherein each second pair represents unrelated entities.
  4. 4. The method of any preceding claim, wherein the classifier evaluates features of each record, including at least one of a word overlap count, word frequency, a word-based or character based cosine similarity, merchant category codes, and numeric city codcs associatcd with cach rccord.
  5. 5. The method of any preceding claim, wherein the classifier evaluates features of each record including a at least one of a fractional difference in size of an average ticket-size in the record, a standard deviation between the average ticket-sizes in the records, and a fractional difference in a magnitude of ticket-size variances
  6. 6. The method of any preceding claim, wherein resolving the record set to the exemplar record set comprises: merging the records of the record set into the exemplar record set.
  7. 7. The method of any preceding claim, further comprising, performing an analysis on a set of the records, wherein the set includes the records of the exemplar record set and the records resolved as associated with the first entity.
  8. 8. The method of claim 10, further comprising determining, for each transaction jo record set, aggregate values for the attributes of the transaction record set; and determining aggregate values for attributes of the exemplar record set.
  9. 9. The method of any preceding claim, wherein the records are financial transaction records, e.g. comprising credit or debit transactions processed by a financial institution for a merchant.
  10. 10. The method of daim 9, wherein attributes of the financial transaction records include one or more of the following: an identification of the merchant from which the financial transaction originates; an identification of the credit or debit account owner; an amonnt of the financial transaction; a date of the financial transaction; a time of the financial transaction; and a location of where the financial transaction originated.
  11. ii. A computer program comprising machine readable instructions that when executed by computing apparatus causes it to perform the method of any preceding claim.
  12. 12. A computer system, comprising: a memory; and a processor storing one or more programs configured to perform an operation for identifying related transaction records from a database storing records for multiple entities, the method comprising: retrieving a plurality of record sets, wherein each record set includes one or more of the records sharing a common attribute value; receiving a selection of or selecting an exemplar record set, wherein the exemplar record set comprises a plurality of the records associated with a first entity; for each of the plurality of record sets: determining a probability that the record set stores records associated with the first entity by passing a record set and the exemplar record set to a classifier, wherein the classifier is configured to determine the probability that the record set stores records associated with the first entity, and Jo upon determining the probability exceeds a threshold, resoFving the record set as storing records associated with the first entity.
  13. 13. The system of claim 12, wherein the classifier is a random forest classifier.
  14. 14. The system of claim 12 or daim 13, further comprising, training the classifier using a p'urality of training examp'es, the training examples comprising: one or more first pairs of record sets, wherein each first pair represent a common entity; and one or more second pairs of record sets, wherein each second pair represents unrelated entities.
  15. 15. The system of any of claims 12 to 14, wherein resolving the record set to the exemplar record set comprises: merging the records of the record set into the exemplar record set.
  16. i6. The system of any of claims 12 to 15, further comprising, performing an analysis on a set of the records, wherein the set includes the records of the exemplar record set and the records resolved as associated with the first entity.
  17. 17. The system of any of claims 12 to 16, wherein determining a probability comprises passing a transaction record set and the exemplar record set to a classifier, wherein the classifier is configured to determine the probability that the transaction record set stores transaction records associated with the first entity.
  18. 18. The system of any of claims 12 to 17, further comprising determining, for each transaction record set, aggregate values for the attributes of the transaction record set; and determining aggregate values for attributes of the exemplar record set.
  19. 19. The system of any of claims 12 to 18, wherein the transaction records are financial transaction records, e.g. comprising credit or debit transactions processed by a financial institution for a merchant.o
  20. 20. The system of claim 19, wherein attributes of the financial transaction records include one or more of the following: an identification of the merchant from which the financial transaction originates; an identification of the credit or debit account owner; an amount of the financial transaction; a date of the financial transaction; a time of the financial transaction; and a ocation of where the financial transaction originated.
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Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9286373B2 (en) 2013-03-15 2016-03-15 Palantir Technologies Inc. Computer-implemented systems and methods for comparing and associating objects
US9348499B2 (en) 2008-09-15 2016-05-24 Palantir Technologies, Inc. Sharing objects that rely on local resources with outside servers
US9392008B1 (en) 2015-07-23 2016-07-12 Palantir Technologies Inc. Systems and methods for identifying information related to payment card breaches
US9483546B2 (en) 2014-12-15 2016-11-01 Palantir Technologies Inc. System and method for associating related records to common entities across multiple lists
US9495353B2 (en) 2013-03-15 2016-11-15 Palantir Technologies Inc. Method and system for generating a parser and parsing complex data
US9501552B2 (en) 2007-10-18 2016-11-22 Palantir Technologies, Inc. Resolving database entity information
US9514414B1 (en) 2015-12-11 2016-12-06 Palantir Technologies Inc. Systems and methods for identifying and categorizing electronic documents through machine learning
US9715518B2 (en) 2012-01-23 2017-07-25 Palantir Technologies, Inc. Cross-ACL multi-master replication
US9760556B1 (en) 2015-12-11 2017-09-12 Palantir Technologies Inc. Systems and methods for annotating and linking electronic documents
US9880987B2 (en) 2011-08-25 2018-01-30 Palantir Technologies, Inc. System and method for parameterizing documents for automatic workflow generation
US9898335B1 (en) 2012-10-22 2018-02-20 Palantir Technologies Inc. System and method for batch evaluation programs
US9984428B2 (en) 2015-09-04 2018-05-29 Palantir Technologies Inc. Systems and methods for structuring data from unstructured electronic data files
US9996229B2 (en) 2013-10-03 2018-06-12 Palantir Technologies Inc. Systems and methods for analyzing performance of an entity
US10061828B2 (en) 2006-11-20 2018-08-28 Palantir Technologies, Inc. Cross-ontology multi-master replication
US10103953B1 (en) 2015-05-12 2018-10-16 Palantir Technologies Inc. Methods and systems for analyzing entity performance
US10127289B2 (en) 2015-08-19 2018-11-13 Palantir Technologies Inc. Systems and methods for automatic clustering and canonical designation of related data in various data structures
US10133588B1 (en) 2016-10-20 2018-11-20 Palantir Technologies Inc. Transforming instructions for collaborative updates
US10140664B2 (en) 2013-03-14 2018-11-27 Palantir Technologies Inc. Resolving similar entities from a transaction database
US10146853B2 (en) 2015-05-15 2018-12-04 International Business Machines Corporation Determining entity relationship when entities contain other entities
US10180977B2 (en) 2014-03-18 2019-01-15 Palantir Technologies Inc. Determining and extracting changed data from a data source
US10198515B1 (en) 2013-12-10 2019-02-05 Palantir Technologies Inc. System and method for aggregating data from a plurality of data sources
US10235533B1 (en) 2017-12-01 2019-03-19 Palantir Technologies Inc. Multi-user access controls in electronic simultaneously editable document editor

Families Citing this family (44)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9230280B1 (en) 2013-03-15 2016-01-05 Palantir Technologies Inc. Clustering data based on indications of financial malfeasance
US8868486B2 (en) 2013-03-15 2014-10-21 Palantir Technologies Inc. Time-sensitive cube
US8799799B1 (en) 2013-05-07 2014-08-05 Palantir Technologies Inc. Interactive geospatial map
US9830325B1 (en) * 2013-09-11 2017-11-28 Intuit Inc. Determining a likelihood that two entities are the same
US9785317B2 (en) 2013-09-24 2017-10-10 Palantir Technologies Inc. Presentation and analysis of user interaction data
US8812960B1 (en) 2013-10-07 2014-08-19 Palantir Technologies Inc. Cohort-based presentation of user interaction data
US9734217B2 (en) 2013-12-16 2017-08-15 Palantir Technologies Inc. Methods and systems for analyzing entity performance
US8832832B1 (en) 2014-01-03 2014-09-09 Palantir Technologies Inc. IP reputation
IN2014MU00169A (en) * 2014-01-17 2015-08-28 Tata Consultancy Services Limited Entity resolution from documents
US9904959B2 (en) * 2014-06-09 2018-02-27 Verifi, Inc. Descriptor exchange
US9619557B2 (en) 2014-06-30 2017-04-11 Palantir Technologies, Inc. Systems and methods for key phrase characterization of documents
US9129219B1 (en) 2014-06-30 2015-09-08 Palantir Technologies, Inc. Crime risk forecasting
US9535974B1 (en) 2014-06-30 2017-01-03 Palantir Technologies Inc. Systems and methods for identifying key phrase clusters within documents
US9256664B2 (en) 2014-07-03 2016-02-09 Palantir Technologies Inc. System and method for news events detection and visualization
US9390086B2 (en) 2014-09-11 2016-07-12 Palantir Technologies Inc. Classification system with methodology for efficient verification
US9767172B2 (en) 2014-10-03 2017-09-19 Palantir Technologies Inc. Data aggregation and analysis system
US9229952B1 (en) 2014-11-05 2016-01-05 Palantir Technologies, Inc. History preserving data pipeline system and method
US9043894B1 (en) 2014-11-06 2015-05-26 Palantir Technologies Inc. Malicious software detection in a computing system
US10108623B2 (en) 2014-12-12 2018-10-23 International Business Machines Corporation Merging database operations for serializable transaction execution
US9348920B1 (en) 2014-12-22 2016-05-24 Palantir Technologies Inc. Concept indexing among database of documents using machine learning techniques
US9335911B1 (en) 2014-12-29 2016-05-10 Palantir Technologies Inc. Interactive user interface for dynamic data analysis exploration and query processing
US9817563B1 (en) 2014-12-29 2017-11-14 Palantir Technologies Inc. System and method of generating data points from one or more data stores of data items for chart creation and manipulation
US9727560B2 (en) 2015-02-25 2017-08-08 Palantir Technologies Inc. Systems and methods for organizing and identifying documents via hierarchies and dimensions of tags
EP3070622A1 (en) 2015-03-16 2016-09-21 Palantir Technologies, Inc. Interactive user interfaces for location-based data analysis
US9886467B2 (en) 2015-03-19 2018-02-06 Plantir Technologies Inc. System and method for comparing and visualizing data entities and data entity series
US9904916B2 (en) * 2015-07-01 2018-02-27 Klarna Ab Incremental login and authentication to user portal without username/password
US9996595B2 (en) 2015-08-03 2018-06-12 Palantir Technologies, Inc. Providing full data provenance visualization for versioned datasets
US9671776B1 (en) 2015-08-20 2017-06-06 Palantir Technologies Inc. Quantifying, tracking, and anticipating risk at a manufacturing facility, taking deviation type and staffing conditions into account
US9485265B1 (en) 2015-08-28 2016-11-01 Palantir Technologies Inc. Malicious activity detection system capable of efficiently processing data accessed from databases and generating alerts for display in interactive user interfaces
US9639580B1 (en) 2015-09-04 2017-05-02 Palantir Technologies, Inc. Computer-implemented systems and methods for data management and visualization
US9576015B1 (en) 2015-09-09 2017-02-21 Palantir Technologies, Inc. Domain-specific language for dataset transformations
US9424669B1 (en) 2015-10-21 2016-08-23 Palantir Technologies Inc. Generating graphical representations of event participation flow
US10235725B2 (en) * 2015-11-09 2019-03-19 Mastercard International Incorporated Method and system for determining merchant gratuity values
US10114884B1 (en) 2015-12-16 2018-10-30 Palantir Technologies Inc. Systems and methods for attribute analysis of one or more databases
US20170177655A1 (en) * 2015-12-17 2017-06-22 SpringAhead, Inc. Dynamic data normalization and duplicate analysis
US9792020B1 (en) 2015-12-30 2017-10-17 Palantir Technologies Inc. Systems for collecting, aggregating, and storing data, generating interactive user interfaces for analyzing data, and generating alerts based upon collected data
US9652139B1 (en) 2016-04-06 2017-05-16 Palantir Technologies Inc. Graphical representation of an output
US10068199B1 (en) 2016-05-13 2018-09-04 Palantir Technologies Inc. System to catalogue tracking data
US10007674B2 (en) 2016-06-13 2018-06-26 Palantir Technologies Inc. Data revision control in large-scale data analytic systems
US9842338B1 (en) 2016-11-21 2017-12-12 Palantir Technologies Inc. System to identify vulnerable card readers
US9886525B1 (en) 2016-12-16 2018-02-06 Palantir Technologies Inc. Data item aggregate probability analysis system
US10249033B1 (en) 2016-12-20 2019-04-02 Palantir Technologies Inc. User interface for managing defects
US10133621B1 (en) 2017-01-18 2018-11-20 Palantir Technologies Inc. Data analysis system to facilitate investigative process
US10133783B2 (en) 2017-04-11 2018-11-20 Palantir Technologies Inc. Systems and methods for constraint driven database searching

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110099133A1 (en) * 2009-10-28 2011-04-28 Industrial Technology Research Institute Systems and methods for capturing and managing collective social intelligence information
CN102054015A (en) * 2009-10-28 2011-05-11 财团法人工业技术研究院 System and method of organizing community intelligent information by using organic matter data model
US20130166480A1 (en) * 2011-12-21 2013-06-27 Telenav, Inc. Navigation system with point of interest classification mechanism and method of operation thereof

Family Cites Families (411)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5241625A (en) 1990-11-27 1993-08-31 Farallon Computing, Inc. Screen image sharing among heterogeneous computers
US6101479A (en) 1992-07-15 2000-08-08 Shaw; James G. System and method for allocating company resources to fulfill customer expectations
US5819226A (en) 1992-09-08 1998-10-06 Hnc Software Inc. Fraud detection using predictive modeling
US5777549A (en) 1995-03-29 1998-07-07 Cabletron Systems, Inc. Method and apparatus for policy-based alarm notification in a distributed network management environment
US6094643A (en) 1996-06-14 2000-07-25 Card Alert Services, Inc. System for detecting counterfeit financial card fraud
US5878434A (en) 1996-07-18 1999-03-02 Novell, Inc Transaction clash management in a disconnectable computer and network
US5832218A (en) 1995-12-14 1998-11-03 International Business Machines Corporation Client/server electronic mail system for providng off-line client utilization and seamless server resynchronization
US6006242A (en) 1996-04-05 1999-12-21 Bankers Systems, Inc. Apparatus and method for dynamically creating a document
US5845300A (en) 1996-06-05 1998-12-01 Microsoft Corporation Method and apparatus for suggesting completions for a partially entered data item based on previously-entered, associated data items
US5897636A (en) 1996-07-11 1999-04-27 Tandem Corporation Incorporated Distributed object computer system with hierarchical name space versioning
US5892900A (en) 1996-08-30 1999-04-06 Intertrust Technologies Corp. Systems and methods for secure transaction management and electronic rights protection
US5826021A (en) 1996-09-17 1998-10-20 Sun Microsystems, Inc. Disconnected write authorization in a client/server computing system
US5870559A (en) 1996-10-15 1999-02-09 Mercury Interactive Software system and associated methods for facilitating the analysis and management of web sites
CA2190043C (en) 1996-11-12 2001-10-16 Don E. Hameluck Buffered screen capturing software tool usability testing of computer applications
US6430305B1 (en) * 1996-12-20 2002-08-06 Synaptics, Incorporated Identity verification methods
US6065026A (en) 1997-01-09 2000-05-16 Document.Com, Inc. Multi-user electronic document authoring system with prompted updating of shared language
US9053222B2 (en) 2002-05-17 2015-06-09 Lawrence A. Lynn Patient safety processor
US5966706A (en) 1997-02-19 1999-10-12 At&T Corp Local logging in a distributed database management computer system
US6026233A (en) 1997-05-27 2000-02-15 Microsoft Corporation Method and apparatus for presenting and selecting options to modify a programming language statement
US7403922B1 (en) 1997-07-28 2008-07-22 Cybersource Corporation Method and apparatus for evaluating fraud risk in an electronic commerce transaction
US6463404B1 (en) 1997-08-08 2002-10-08 British Telecommunications Public Limited Company Translation
US6134582A (en) 1998-05-26 2000-10-17 Microsoft Corporation System and method for managing electronic mail messages using a client-based database
US7168039B2 (en) 1998-06-02 2007-01-23 International Business Machines Corporation Method and system for reducing the horizontal space required for displaying a column containing text data
US6243706B1 (en) 1998-07-24 2001-06-05 Avid Technology, Inc. System and method for managing the creation and production of computer generated works
US6243717B1 (en) 1998-09-01 2001-06-05 Camstar Systems, Inc. System and method for implementing revision management of linked data entities and user dependent terminology
US6232971B1 (en) 1998-09-23 2001-05-15 International Business Machines Corporation Variable modality child windows
US7213030B1 (en) 1998-10-16 2007-05-01 Jenkins Steven R Web-enabled transaction and collaborative management system
US6560578B2 (en) 1999-03-12 2003-05-06 Expanse Networks, Inc. Advertisement selection system supporting discretionary target market characteristics
US7418399B2 (en) 1999-03-10 2008-08-26 Illinois Institute Of Technology Methods and kits for managing diagnosis and therapeutics of bacterial infections
US7373592B2 (en) 1999-07-30 2008-05-13 Microsoft Corporation Modeless child windows for application programs
AU4019901A (en) 1999-09-21 2001-04-24 Andrew E. Borthwick A probabilistic record linkage model derived from training data
US6523019B1 (en) 1999-09-21 2003-02-18 Choicemaker Technologies, Inc. Probabilistic record linkage model derived from training data
US6519627B1 (en) 1999-09-27 2003-02-11 International Business Machines Corporation System and method for conducting disconnected transactions with service contracts for pervasive computing devices
WO2001025906A1 (en) 1999-10-01 2001-04-12 Global Graphics Software Limited Method and system for arranging a workflow using graphical user interface
US8091784B1 (en) * 2005-03-09 2012-01-10 Diebold, Incorporated Banking system controlled responsive to data bearing records
US6944821B1 (en) 1999-12-07 2005-09-13 International Business Machines Corporation Copy/paste mechanism and paste buffer that includes source information for copied data
US20040117387A1 (en) 2000-02-25 2004-06-17 Vincent Civetta Database sizing and diagnostic utility
US20020032677A1 (en) 2000-03-01 2002-03-14 Jeff Morgenthaler Methods for creating, editing, and updating searchable graphical database and databases of graphical images and information and displaying graphical images from a searchable graphical database or databases in a sequential or slide show format
JP2001283120A (en) 2000-03-31 2001-10-12 Oki Electric Ind Co Ltd Transaction supporting system
DE60111376T2 (en) 2000-05-16 2006-03-16 O'carroll, Garrett System and method for document processing
US8386945B1 (en) 2000-05-17 2013-02-26 Eastman Kodak Company System and method for implementing compound documents in a production printing workflow
GB2366498A (en) 2000-08-25 2002-03-06 Copyn Ltd Method of bookmarking a section of a web-page and storing said bookmarks
US6795868B1 (en) 2000-08-31 2004-09-21 Data Junction Corp. System and method for event-driven data transformation
TWI244617B (en) 2000-09-16 2005-12-01 Ibm A client/server-based data processing system for performing transactions between clients and a server and a method of performing the transactions
US20020065708A1 (en) 2000-09-22 2002-05-30 Hikmet Senay Method and system for interactive visual analyses of organizational interactions
US8707185B2 (en) 2000-10-10 2014-04-22 Addnclick, Inc. Dynamic information management system and method for content delivery and sharing in content-, metadata- and viewer-based, live social networking among users concurrently engaged in the same and/or similar content
US6754640B2 (en) * 2000-10-30 2004-06-22 William O. Bozeman Universal positive pay match, authentication, authorization, settlement and clearing system
US6978419B1 (en) 2000-11-15 2005-12-20 Justsystem Corporation Method and apparatus for efficient identification of duplicate and near-duplicate documents and text spans using high-discriminability text fragments
US7058648B1 (en) 2000-12-01 2006-06-06 Oracle International Corporation Hierarchy-based secured document repository
US20020103705A1 (en) * 2000-12-06 2002-08-01 Forecourt Communication Group Method and apparatus for using prior purchases to select activities to present to a customer
US7529698B2 (en) * 2001-01-16 2009-05-05 Raymond Anthony Joao Apparatus and method for providing transaction history information, account history information, and/or charge-back information
US7921123B2 (en) 2001-02-20 2011-04-05 Hartford Fire Insurance Company Method and system for processing physician claims over a network
US20100057622A1 (en) * 2001-02-27 2010-03-04 Faith Patrick L Distributed Quantum Encrypted Pattern Generation And Scoring
US6980984B1 (en) 2001-05-16 2005-12-27 Kanisa, Inc. Content provider systems and methods using structured data
US7877421B2 (en) 2001-05-25 2011-01-25 International Business Machines Corporation Method and system for mapping enterprise data assets to a semantic information model
US20040205492A1 (en) 2001-07-26 2004-10-14 Newsome Mark R. Content clipping service
US20030036927A1 (en) 2001-08-20 2003-02-20 Bowen Susan W. Healthcare information search system and user interface
US20030061132A1 (en) 2001-09-26 2003-03-27 Yu, Mason K. System and method for categorizing, aggregating and analyzing payment transactions data
US7058567B2 (en) 2001-10-10 2006-06-06 Xerox Corporation Natural language parser
US6877136B2 (en) 2001-10-26 2005-04-05 United Services Automobile Association (Usaa) System and method of providing electronic access to one or more documents
US7756728B2 (en) 2001-10-31 2010-07-13 Siemens Medical Solutions Usa, Inc. Healthcare system and user interface for consolidating patient related information from different sources
US20120065987A1 (en) 2010-09-09 2012-03-15 Siemens Medical Solutions Usa, Inc. Computer-Based Patient Management for Healthcare
US6876996B2 (en) 2001-11-14 2005-04-05 Sun Microsystems, Inc. Method and apparatus for using a shared library mechanism to facilitate sharing of metadata
US7089541B2 (en) 2001-11-30 2006-08-08 Sun Microsystems, Inc. Modular parser architecture with mini parsers
US7475242B2 (en) 2001-12-18 2009-01-06 Hewlett-Packard Development Company, L.P. Controlling the distribution of information
US7174377B2 (en) 2002-01-16 2007-02-06 Xerox Corporation Method and apparatus for collaborative document versioning of networked documents
US7225183B2 (en) 2002-01-28 2007-05-29 Ipxl, Inc. Ontology-based information management system and method
US7813937B1 (en) 2002-02-15 2010-10-12 Fair Isaac Corporation Consistency modeling of healthcare claims to detect fraud and abuse
US20030171942A1 (en) 2002-03-06 2003-09-11 I-Centrix Llc Contact relationship management system and method
US6993539B2 (en) 2002-03-19 2006-01-31 Network Appliance, Inc. System and method for determining changes in two snapshots and for transmitting changes to destination snapshot
AU2002323166A1 (en) * 2002-03-20 2003-10-08 Catalina Marketing International Inc. Targeted incentives based upon predicted behavior
US7533026B2 (en) 2002-04-12 2009-05-12 International Business Machines Corporation Facilitating management of service elements usable in providing information technology service offerings
US7426559B2 (en) 2002-05-09 2008-09-16 International Business Machines Corporation Method for sequential coordination of external database application events with asynchronous internal database events
US7539680B2 (en) 2002-05-10 2009-05-26 Lsi Corporation Revision control for database of evolved design
US8232725B1 (en) 2002-05-21 2012-07-31 Imaging Systems Technology Plasma-tube gas discharge device
US20040044648A1 (en) 2002-06-24 2004-03-04 Xmyphonic System As Method for data-centric collaboration
US6996583B2 (en) 2002-07-01 2006-02-07 International Business Machines Corporation Real-time database update transaction with disconnected relational database clients
US20040006523A1 (en) 2002-07-08 2004-01-08 Coker Don W. System and method for preventing financial fraud
US7461158B2 (en) 2002-08-07 2008-12-02 Intelliden, Inc. System and method for controlling access rights to network resources
US7076508B2 (en) 2002-08-12 2006-07-11 International Business Machines Corporation Method, system, and program for merging log entries from multiple recovery log files
US8799023B2 (en) 2002-10-18 2014-08-05 Medimpact Healthcare Systems, Inc. Mass customization for management of healthcare
GB0224589D0 (en) 2002-10-22 2002-12-04 British Telecomm Method and system for processing or searching user records
US20040083466A1 (en) 2002-10-29 2004-04-29 Dapp Michael C. Hardware parser accelerator
US20040088177A1 (en) 2002-11-04 2004-05-06 Electronic Data Systems Corporation Employee performance management method and system
CN1757188A (en) 2002-11-06 2006-04-05 国际商业机器公司 Confidential data sharing and anonymous entity resolution
WO2004046957A2 (en) 2002-11-15 2004-06-03 Creo Inc. Methods and systems for sharing data
US20040111480A1 (en) 2002-12-09 2004-06-10 Yue Jonathan Zhanjun Message screening system and method
US8589273B2 (en) 2002-12-23 2013-11-19 Ge Corporate Financial Services, Inc. Methods and systems for managing risk management information
US7752117B2 (en) 2003-01-31 2010-07-06 Trading Technologies International, Inc. System and method for money management in electronic trading environment
US7403942B1 (en) 2003-02-04 2008-07-22 Seisint, Inc. Method and system for processing data records
US7912842B1 (en) 2003-02-04 2011-03-22 Lexisnexis Risk Data Management Inc. Method and system for processing and linking data records
US20040153418A1 (en) 2003-02-05 2004-08-05 Hanweck Gerald Alfred System and method for providing access to data from proprietary tools
US8386377B1 (en) 2003-05-12 2013-02-26 Id Analytics, Inc. System and method for credit scoring using an identity network connectivity
US7809650B2 (en) 2003-07-01 2010-10-05 Visa U.S.A. Inc. Method and system for providing risk information in connection with transaction processing
US8412566B2 (en) * 2003-07-08 2013-04-02 Yt Acquisition Corporation High-precision customer-based targeting by individual usage statistics
AU2003903994A0 (en) 2003-07-31 2003-08-14 Canon Kabushiki Kaisha Collaborative editing with automatic layout
US20090132347A1 (en) * 2003-08-12 2009-05-21 Russell Wayne Anderson Systems And Methods For Aggregating And Utilizing Retail Transaction Records At The Customer Level
WO2005036319A2 (en) * 2003-09-22 2005-04-21 Catalina Marketing International, Inc. Assumed demographics, predicted behaviour, and targeted incentives
US7584172B2 (en) 2003-10-16 2009-09-01 Sap Ag Control for selecting data query and visual configuration
US20050091186A1 (en) 2003-10-24 2005-04-28 Alon Elish Integrated method and apparatus for capture, storage, and retrieval of information
US8627489B2 (en) 2003-10-31 2014-01-07 Adobe Systems Incorporated Distributed document version control
US7080104B2 (en) 2003-11-07 2006-07-18 Plaxo, Inc. Synchronization and merge engines
US20050131935A1 (en) 2003-11-18 2005-06-16 O'leary Paul J. Sector content mining system using a modular knowledge base
US20050125715A1 (en) 2003-12-04 2005-06-09 Fabrizio Di Franco Method of saving data in a graphical user interface
US6948656B2 (en) 2003-12-23 2005-09-27 First Data Corporation System with GPS to manage risk of financial transactions
US7917376B2 (en) 2003-12-29 2011-03-29 Montefiore Medical Center System and method for monitoring patient care
US8725493B2 (en) 2004-01-06 2014-05-13 Neuric Llc Natural language parsing method to provide conceptual flow
US20050154628A1 (en) 2004-01-13 2005-07-14 Illumen, Inc. Automated management of business performance information
US20050154769A1 (en) 2004-01-13 2005-07-14 Llumen, Inc. Systems and methods for benchmarking business performance data against aggregated business performance data
US7853533B2 (en) 2004-03-02 2010-12-14 The 41St Parameter, Inc. Method and system for identifying users and detecting fraud by use of the internet
US20060026120A1 (en) 2004-03-24 2006-02-02 Update Publications Lp Method and system for collecting, processing, and distributing residential property data
US20060031779A1 (en) 2004-04-15 2006-02-09 Citrix Systems, Inc. Selectively sharing screen data
US8041701B2 (en) 2004-05-04 2011-10-18 DG FastChannel, Inc Enhanced graphical interfaces for displaying visual data
US7689601B2 (en) 2004-05-06 2010-03-30 Oracle International Corporation Achieving web documents using unique document locators
US7587721B2 (en) 2004-05-20 2009-09-08 Sap Ag Sharing objects in runtime systems
US7415704B2 (en) 2004-05-20 2008-08-19 Sap Ag Sharing objects in runtime systems
EP1769435A1 (en) 2004-05-25 2007-04-04 Arion Human Capital Limited Data analysis and flow control system
CA2564533A1 (en) 2004-05-25 2005-12-08 Postini, Inc. Electronic message source information reputation system
US8161122B2 (en) 2005-06-03 2012-04-17 Messagemind, Inc. System and method of dynamically prioritized electronic mail graphical user interface, and measuring email productivity and collaboration trends
US8924469B2 (en) 2008-06-05 2014-12-30 Headwater Partners I Llc Enterprise access control and accounting allocation for access networks
US20060010130A1 (en) 2004-07-09 2006-01-12 Avraham Leff Method and apparatus for synchronizing client transactions executed by an autonomous client
US7870487B2 (en) 2004-07-29 2011-01-11 International Business Machines Corporation Inserting into a document a screen image of a computer software application
US7552116B2 (en) 2004-08-06 2009-06-23 The Board Of Trustees Of The University Of Illinois Method and system for extracting web query interfaces
WO2006018843A2 (en) 2004-08-16 2006-02-23 Beinsync Ltd. A system and method for the synchronization of data across multiple computing devices
US7617232B2 (en) 2004-09-02 2009-11-10 Microsoft Corporation Centralized terminology and glossary development
US7493333B2 (en) 2004-09-03 2009-02-17 Biowisdom Limited System and method for parsing and/or exporting data from one or more multi-relational ontologies
US20060059423A1 (en) 2004-09-13 2006-03-16 Stefan Lehmann Apparatus, system, and method for creating customized workflow documentation
US20060080316A1 (en) 2004-10-08 2006-04-13 Meridio Ltd Multiple indexing of an electronic document to selectively permit access to the content and metadata thereof
US20060080139A1 (en) 2004-10-08 2006-04-13 Woodhaven Health Services Preadmission health care cost and reimbursement estimation tool
US8892571B2 (en) 2004-10-12 2014-11-18 International Business Machines Corporation Systems for associating records in healthcare database with individuals
US7739246B2 (en) 2004-10-14 2010-06-15 Microsoft Corporation System and method of merging contacts
US7757220B2 (en) 2004-10-21 2010-07-13 Discovery Machine, Inc. Computer interchange of knowledge hierarchies
US7797197B2 (en) 2004-11-12 2010-09-14 Amazon Technologies, Inc. Method and system for analyzing the performance of affiliate sites
US8938434B2 (en) 2004-11-22 2015-01-20 Intelius, Inc. Household grouping based on public records
US7899796B1 (en) 2004-11-23 2011-03-01 Andrew Borthwick Batch automated blocking and record matching
US20060178954A1 (en) 2004-12-13 2006-08-10 Rohit Thukral Iterative asset reconciliation process
US20060129746A1 (en) 2004-12-14 2006-06-15 Ithink, Inc. Method and graphic interface for storing, moving, sending or printing electronic data to two or more locations, in two or more formats with a single save function
US7451397B2 (en) 2004-12-15 2008-11-11 Microsoft Corporation System and method for automatically completing spreadsheet formulas
US9020887B2 (en) 2004-12-21 2015-04-28 Proofpoint, Inc. Managing the status of documents in a distributed storage system
US20060143079A1 (en) 2004-12-29 2006-06-29 Jayanta Basak Cross-channel customer matching
US8700414B2 (en) 2004-12-29 2014-04-15 Sap Ag System supported optimization of event resolution
US8271436B2 (en) 2005-02-07 2012-09-18 Mimosa Systems, Inc. Retro-fitting synthetic full copies of data
US20060190295A1 (en) 2005-02-22 2006-08-24 Richard Merkin Systems and methods for assessing and optimizing healthcare administration
WO2006102270A2 (en) 2005-03-22 2006-09-28 Cooper Kim A Performance motivation systems and methods for contact centers
US20060218491A1 (en) 2005-03-25 2006-09-28 International Business Machines Corporation System, method and program product for community review of documents
US7596528B1 (en) 2005-03-31 2009-09-29 Trading Technologies International, Inc. System and method for dynamically regulating order entry in an electronic trading environment
US8145686B2 (en) 2005-05-06 2012-03-27 Microsoft Corporation Maintenance of link level consistency between database and file system
US7672968B2 (en) 2005-05-12 2010-03-02 Apple Inc. Displaying a tooltip associated with a concurrently displayed database object
US20060277460A1 (en) 2005-06-03 2006-12-07 Scott Forstall Webview applications
EP1732034A1 (en) * 2005-06-06 2006-12-13 First Data Corporation System and method for authorizing electronic payment transactions
US8341259B2 (en) 2005-06-06 2012-12-25 Adobe Systems Incorporated ASP for web analytics including a real-time segmentation workbench
WO2007002702A2 (en) 2005-06-24 2007-01-04 Fair Isaac Corporation Mass compromise / point of compromise analytic detection and compromised card portfolio management system
US8285639B2 (en) 2005-07-05 2012-10-09 mConfirm, Ltd. Location based authentication system
US8429527B1 (en) 2005-07-12 2013-04-23 Open Text S.A. Complex data merging, such as in a workflow application
US7991764B2 (en) 2005-07-22 2011-08-02 Yogesh Chunilal Rathod Method and system for communication, publishing, searching, sharing and dynamically providing a journal feed
US7421429B2 (en) 2005-08-04 2008-09-02 Microsoft Corporation Generate blog context ranking using track-back weight, context weight and, cumulative comment weight
US20090168163A1 (en) 2005-11-01 2009-07-02 Global Bionic Optics Pty Ltd. Optical lens systems
US7529726B2 (en) 2005-08-22 2009-05-05 International Business Machines Corporation XML sub-document versioning method in XML databases using record storages
US8095866B2 (en) 2005-09-09 2012-01-10 Microsoft Corporation Filtering user interface for a data summary table
US7958147B1 (en) 2005-09-13 2011-06-07 James Luke Turner Method for providing customized and automated security assistance, a document marking regime, and central tracking and control for sensitive or classified documents in electronic format
US7941336B1 (en) 2005-09-14 2011-05-10 D2C Solutions, LLC Segregation-of-duties analysis apparatus and method
US8468441B2 (en) 2005-09-15 2013-06-18 Microsoft Corporation Cross-application support of charts
US7672833B2 (en) 2005-09-22 2010-03-02 Fair Isaac Corporation Method and apparatus for automatic entity disambiguation
US8306986B2 (en) 2005-09-30 2012-11-06 American Express Travel Related Services Company, Inc. Method, system, and computer program product for linking customer information
US7668769B2 (en) 2005-10-04 2010-02-23 Basepoint Analytics, LLC System and method of detecting fraud
US20070178501A1 (en) 2005-12-06 2007-08-02 Matthew Rabinowitz System and method for integrating and validating genotypic, phenotypic and medical information into a database according to a standardized ontology
US8147715B2 (en) 2005-12-08 2012-04-03 National Institute For Materials Science Phosphor, process for producing the same, and luminescent device
US20070136095A1 (en) 2005-12-09 2007-06-14 Arizona Board Of Regents On Behalf Of The University Of Arizona Icon Queues for Workflow Management
US7606844B2 (en) 2005-12-19 2009-10-20 Commvault Systems, Inc. System and method for performing replication copy storage operations
US8726144B2 (en) 2005-12-23 2014-05-13 Xerox Corporation Interactive learning-based document annotation
US7788296B2 (en) 2005-12-29 2010-08-31 Guidewire Software, Inc. Method and apparatus for managing a computer-based address book for incident-related work
US8712828B2 (en) 2005-12-30 2014-04-29 Accenture Global Services Limited Churn prediction and management system
US20070185867A1 (en) 2006-02-03 2007-08-09 Matteo Maga Statistical modeling methods for determining customer distribution by churn probability within a customer population
US7490298B2 (en) 2006-04-12 2009-02-10 International Business Machines Corporation Creating documentation screenshots on demand
US7756843B1 (en) 2006-05-25 2010-07-13 Juniper Networks, Inc. Identifying and processing confidential information on network endpoints
US20140040371A1 (en) 2009-12-01 2014-02-06 Topsy Labs, Inc. Systems and methods for identifying geographic locations of social media content collected over social networks
US9195985B2 (en) * 2006-06-08 2015-11-24 Iii Holdings 1, Llc Method, system, and computer program product for customer-level data verification
US7866542B2 (en) 2006-06-08 2011-01-11 International Business Machines Corporation System and method for resolving identities that are indefinitely resolvable
JP4218700B2 (en) 2006-06-19 2009-02-04 コニカミノルタビジネステクノロジーズ株式会社 Image forming apparatus
US7720789B2 (en) 2006-06-23 2010-05-18 International Business Machines Corporation System and method of member unique names
US7933955B2 (en) 2006-07-11 2011-04-26 Igor Khalatian One-click universal screen sharing
US20120173381A1 (en) 2011-01-03 2012-07-05 Stanley Benjamin Smith Process and system for pricing and processing weighted data in a federated or subscription based data source
US7747562B2 (en) 2006-08-15 2010-06-29 International Business Machines Corporation Virtual multidimensional datasets for enterprise software systems
US8230332B2 (en) 2006-08-30 2012-07-24 Compsci Resources, Llc Interactive user interface for converting unstructured documents
US8054756B2 (en) 2006-09-18 2011-11-08 Yahoo! Inc. Path discovery and analytics for network data
US9183321B2 (en) 2006-10-16 2015-11-10 Oracle International Corporation Managing compound XML documents in a repository
US20080103798A1 (en) 2006-10-25 2008-05-01 Domenikos Steven D Identity Protection
US7792353B2 (en) 2006-10-31 2010-09-07 Hewlett-Packard Development Company, L.P. Retraining a machine-learning classifier using re-labeled training samples
US8229902B2 (en) 2006-11-01 2012-07-24 Ab Initio Technology Llc Managing storage of individually accessible data units
US8117281B2 (en) 2006-11-02 2012-02-14 Addnclick, Inc. Using internet content as a means to establish live social networks by linking internet users to each other who are simultaneously engaged in the same and/or similar content
US20080109714A1 (en) 2006-11-03 2008-05-08 Sap Ag Capturing screen information
US7657497B2 (en) 2006-11-07 2010-02-02 Ebay Inc. Online fraud prevention using genetic algorithm solution
US7962495B2 (en) 2006-11-20 2011-06-14 Palantir Technologies, Inc. Creating data in a data store using a dynamic ontology
US7853614B2 (en) 2006-11-27 2010-12-14 Rapleaf, Inc. Hierarchical, traceable, and association reputation assessment of email domains
WO2008070860A2 (en) 2006-12-07 2008-06-12 Linker Sheldon O Method and system for machine understanding, knowledge, and conversation
US8126848B2 (en) 2006-12-07 2012-02-28 Robert Edward Wagner Automated method for identifying and repairing logical data discrepancies between database replicas in a database cluster
US8290838B1 (en) * 2006-12-29 2012-10-16 Amazon Technologies, Inc. Indicating irregularities in online financial transactions
EP2111593A2 (en) 2007-01-26 2009-10-28 Information Resources, Inc. Analytic platform
US8171418B2 (en) 2007-01-31 2012-05-01 Salesforce.Com, Inc. Method and system for presenting a visual representation of the portion of the sets of data that a query is expected to return
US20080208735A1 (en) 2007-02-22 2008-08-28 American Expresstravel Related Services Company, Inc., A New York Corporation Method, System, and Computer Program Product for Managing Business Customer Contacts
US7873557B2 (en) 2007-02-28 2011-01-18 Aaron Guidotti Information, document, and compliance management for financial professionals, clients, and supervisors
US8180717B2 (en) 2007-03-20 2012-05-15 President And Fellows Of Harvard College System for estimating a distribution of message content categories in source data
US8036971B2 (en) 2007-03-30 2011-10-11 Palantir Technologies, Inc. Generating dynamic date sets that represent market conditions
US20080255973A1 (en) 2007-04-10 2008-10-16 Robert El Wade Sales transaction analysis tool and associated method of use
US20090164387A1 (en) 2007-04-17 2009-06-25 Semandex Networks Inc. Systems and methods for providing semantically enhanced financial information
US7880921B2 (en) 2007-05-01 2011-02-01 Michael Joseph Dattilo Method and apparatus to digitally whiteout mistakes on a printed form
US7962904B2 (en) 2007-05-10 2011-06-14 Microsoft Corporation Dynamic parser
US7840456B2 (en) * 2007-05-30 2010-11-23 Intuit Inc. System and method for categorizing credit card transaction data
US7930547B2 (en) 2007-06-15 2011-04-19 Alcatel-Lucent Usa Inc. High accuracy bloom filter using partitioned hashing
WO2009009623A1 (en) 2007-07-09 2009-01-15 Tailwalker Technologies, Inc. Integrating a methodology management system with project tasks in a project management system
US7966199B1 (en) 2007-07-19 2011-06-21 Intuit Inc. Method and system for identification of geographic condition zones using aggregated claim data
US8600872B1 (en) 2007-07-27 2013-12-03 Wells Fargo Bank, N.A. System and method for detecting account compromises
US8156166B2 (en) 2007-08-06 2012-04-10 Intuit Inc. Method and apparatus for selecting a doctor based on an observed experience level
US20130275186A1 (en) * 2007-08-14 2013-10-17 Visa U.S.A. Inc. Merchant Benchmarking Tool
US7761525B2 (en) 2007-08-23 2010-07-20 International Business Machines Corporation System and method for providing improved time references in documents
US8631015B2 (en) 2007-09-06 2014-01-14 Linkedin Corporation Detecting associates
WO2009039391A1 (en) 2007-09-21 2009-03-26 The Methodist Hospital System Systems, methods and apparatuses for generating and using representations of individual or aggregate human medical data
EP2051173A3 (en) 2007-09-27 2009-08-12 Magix Ag System and method for dynamic content insertion from the internet into a multimedia work
US8849728B2 (en) 2007-10-01 2014-09-30 Purdue Research Foundation Visual analytics law enforcement tools
US8484115B2 (en) 2007-10-03 2013-07-09 Palantir Technologies, Inc. Object-oriented time series generator
US20090094270A1 (en) 2007-10-08 2009-04-09 Alirez Baldomero J Method of building a validation database
US8554719B2 (en) 2007-10-18 2013-10-08 Palantir Technologies, Inc. Resolving database entity information
US8214308B2 (en) * 2007-10-23 2012-07-03 Sas Institute Inc. Computer-implemented systems and methods for updating predictive models
US7650310B2 (en) * 2007-10-30 2010-01-19 Intuit Inc. Technique for reducing phishing
US8019709B2 (en) 2007-11-09 2011-09-13 Vantrix Corporation Method and system for rule-based content filtering
US9898767B2 (en) 2007-11-14 2018-02-20 Panjiva, Inc. Transaction facilitating marketplace platform
US20090150868A1 (en) 2007-12-10 2009-06-11 Al Chakra Method and System for Capturing Movie Shots at the Time of an Automated Graphical User Interface Test Failure
US8270577B2 (en) 2007-12-13 2012-09-18 Verizon Patent And Licensing Inc. Multiple visual voicemail mailboxes
US8417715B1 (en) 2007-12-19 2013-04-09 Tilmann Bruckhaus Platform independent plug-in methods and systems for data mining and analytics
US8666976B2 (en) * 2007-12-31 2014-03-04 Mastercard International Incorporated Methods and systems for implementing approximate string matching within a database
US7925652B2 (en) * 2007-12-31 2011-04-12 Mastercard International Incorporated Methods and systems for implementing approximate string matching within a database
US8738486B2 (en) * 2007-12-31 2014-05-27 Mastercard International Incorporated Methods and apparatus for implementing an ensemble merchant prediction system
US8055633B2 (en) 2008-01-21 2011-11-08 International Business Machines Corporation Method, system and computer program product for duplicate detection
KR100915295B1 (en) 2008-01-22 2009-09-03 성균관대학교산학협력단 System and method for search service having a function of automatic classification of search results
US20090199106A1 (en) 2008-02-05 2009-08-06 Sony Ericsson Mobile Communications Ab Communication terminal including graphical bookmark manager
US20090216562A1 (en) 2008-02-22 2009-08-27 Faulkner Judith R Method and apparatus for accommodating diverse healthcare record centers
US8473519B1 (en) 2008-02-25 2013-06-25 Cisco Technology, Inc. Unified communication audit tool
US7765489B1 (en) 2008-03-03 2010-07-27 Shah Shalin N Presenting notifications related to a medical study on a toolbar
US8191766B2 (en) * 2008-03-04 2012-06-05 Mastercard International Incorporated Methods and systems for managing merchant identifiers
US8856088B2 (en) 2008-04-01 2014-10-07 Microsoft Corporation Application-managed file versioning
US8121962B2 (en) * 2008-04-25 2012-02-21 Fair Isaac Corporation Automated entity identification for efficient profiling in an event probability prediction system
US20090282068A1 (en) 2008-05-12 2009-11-12 Shockro John J Semantic packager
WO2009149063A1 (en) 2008-06-02 2009-12-10 Azuki Systems, Inc. Media mashup system
US20090319515A1 (en) 2008-06-02 2009-12-24 Steven Minton System and method for managing entity knowledgebases
US20090307049A1 (en) * 2008-06-05 2009-12-10 Fair Isaac Corporation Soft Co-Clustering of Data
US8301593B2 (en) 2008-06-12 2012-10-30 Gravic, Inc. Mixed mode synchronous and asynchronous replication system
US8860754B2 (en) 2008-06-22 2014-10-14 Tableau Software, Inc. Methods and systems of automatically generating marks in a graphical view
KR20110056502A (en) 2008-08-04 2011-05-30 퀴드, 아이엔씨. Entity performance analysis engines
US8429194B2 (en) 2008-09-15 2013-04-23 Palantir Technologies, Inc. Document-based workflows
US8417561B2 (en) 2008-09-24 2013-04-09 Bank Of America Corporation Market dynamics
CN101685449B (en) 2008-09-26 2012-07-11 国际商业机器公司 Method and system for connecting tables in a plurality of heterogeneous distributed databases
US20100114887A1 (en) 2008-10-17 2010-05-06 Google Inc. Textual Disambiguation Using Social Connections
US8391584B2 (en) 2008-10-20 2013-03-05 Jpmorgan Chase Bank, N.A. Method and system for duplicate check detection
US8306947B2 (en) 2008-10-30 2012-11-06 Hewlett-Packard Development Company, L.P. Replication of operations on objects distributed in a storage system
US7974943B2 (en) 2008-10-30 2011-07-05 Hewlett-Packard Development Company, L.P. Building a synchronized target database
US20100131502A1 (en) 2008-11-25 2010-05-27 Fordham Bradley S Cohort group generation and automatic updating
US8204859B2 (en) 2008-12-10 2012-06-19 Commvault Systems, Inc. Systems and methods for managing replicated database data
US8719350B2 (en) 2008-12-23 2014-05-06 International Business Machines Corporation Email addressee verification
US10115153B2 (en) 2008-12-31 2018-10-30 Fair Isaac Corporation Detection of compromise of merchants, ATMS, and networks
US20100262688A1 (en) 2009-01-21 2010-10-14 Daniar Hussain Systems, methods, and devices for detecting security vulnerabilities in ip networks
US20100191563A1 (en) 2009-01-23 2010-07-29 Doctors' Administrative Solutions, Llc Physician Practice Optimization Tracking
WO2010085773A1 (en) 2009-01-24 2010-07-29 Kontera Technologies, Inc. Hybrid contextual advertising and related content analysis and display techniques
US8073857B2 (en) 2009-02-17 2011-12-06 International Business Machines Corporation Semantics-based data transformation over a wire in mashups
US8473454B2 (en) 2009-03-10 2013-06-25 Xerox Corporation System and method of on-demand document processing
US20100235915A1 (en) 2009-03-12 2010-09-16 Nasir Memon Using host symptoms, host roles, and/or host reputation for detection of host infection
US20100306285A1 (en) 2009-05-28 2010-12-02 Arcsight, Inc. Specifying a Parser Using a Properties File
US9141911B2 (en) 2009-05-29 2015-09-22 Aspen Technology, Inc. Apparatus and method for automated data selection in model identification and adaptation in multivariable process control
US20100306029A1 (en) * 2009-06-01 2010-12-02 Ryan Jolley Cardholder Clusters
US8495151B2 (en) 2009-06-05 2013-07-23 Chandra Bodapati Methods and systems for determining email addresses
US20100313239A1 (en) 2009-06-09 2010-12-09 International Business Machines Corporation Automated access control for rendered output
US8554742B2 (en) * 2009-07-06 2013-10-08 Intelligent Medical Objects, Inc. System and process for record duplication analysis
EP2454661A1 (en) 2009-07-15 2012-05-23 Proviciel - Mlstate System and method for creating a parser generator and associated computer program
US8392556B2 (en) 2009-07-16 2013-03-05 Ca, Inc. Selective reporting of upstream transaction trace data
US9104695B1 (en) 2009-07-27 2015-08-11 Palantir Technologies, Inc. Geotagging structured data
US10242540B2 (en) 2009-09-02 2019-03-26 Fair Isaac Corporation Visualization for payment card transaction fraud analysis
US9280777B2 (en) 2009-09-08 2016-03-08 Target Brands, Inc. Operations dashboard
US20110066497A1 (en) 2009-09-14 2011-03-17 Choicestream, Inc. Personalized advertising and recommendation
US8214490B1 (en) 2009-09-15 2012-07-03 Symantec Corporation Compact input compensating reputation data tracking mechanism
US20110078173A1 (en) 2009-09-30 2011-03-31 Avaya Inc. Social Network User Interface
EP2483640B1 (en) 2009-09-30 2018-05-09 Videojet Technologies, Inc. Thermal ink jet ink composition
US8595058B2 (en) * 2009-10-15 2013-11-26 Visa U.S.A. Systems and methods to match identifiers
US8321360B2 (en) 2009-10-22 2012-11-27 Symantec Corporation Method and system for weighting transactions in a fraud detection system
WO2011050248A2 (en) 2009-10-23 2011-04-28 Cadio, Inc. Analyzing consumer behavior using electronically-captured consumer location data
US20110131130A1 (en) 2009-12-01 2011-06-02 Bank Of America Corporation Integrated risk assessment and management system
US8645478B2 (en) 2009-12-10 2014-02-04 Mcafee, Inc. System and method for monitoring social engineering in a computer network environment
US20110153384A1 (en) 2009-12-17 2011-06-23 Matthew Donald Horne Visual comps builder
WO2011085360A1 (en) * 2010-01-11 2011-07-14 Panjiva, Inc. Evaluating public records of supply transactions for financial investment decisions
US9026552B2 (en) 2010-01-18 2015-05-05 Salesforce.Com, Inc. System and method for linking contact records to company locations
US20110208822A1 (en) 2010-02-22 2011-08-25 Yogesh Chunilal Rathod Method and system for customized, contextual, dynamic and unified communication, zero click advertisement and prospective customers search engine
US20110208565A1 (en) 2010-02-23 2011-08-25 Michael Ross complex process management
US8478709B2 (en) 2010-03-08 2013-07-02 Hewlett-Packard Development Company, L.P. Evaluation of client status for likelihood of churn
US8752054B2 (en) * 2010-03-11 2014-06-10 Avaya Inc. Intelligent merging of transactions based on a variety of criteria
US20110225482A1 (en) 2010-03-15 2011-09-15 Wizpatent Pte Ltd Managing and generating citations in scholarly work
US20110231296A1 (en) 2010-03-16 2011-09-22 UberMedia, Inc. Systems and methods for interacting with messages, authors, and followers
US20110231305A1 (en) 2010-03-19 2011-09-22 Visa U.S.A. Inc. Systems and Methods to Identify Spending Patterns
US8739118B2 (en) 2010-04-08 2014-05-27 Microsoft Corporation Pragmatic mapping specification, compilation and validation
US8306846B2 (en) 2010-04-12 2012-11-06 First Data Corporation Transaction location analytics systems and methods
US20110258216A1 (en) 2010-04-20 2011-10-20 International Business Machines Corporation Usability enhancements for bookmarks of browsers
US8874432B2 (en) 2010-04-28 2014-10-28 Nec Laboratories America, Inc. Systems and methods for semi-supervised relationship extraction
US8255399B2 (en) 2010-04-28 2012-08-28 Microsoft Corporation Data classifier
US8473415B2 (en) 2010-05-04 2013-06-25 Kevin Paul Siegel System and method for identifying a point of compromise in a payment transaction processing system
US20110289397A1 (en) 2010-05-19 2011-11-24 Mauricio Eastmond Displaying Table Data in a Limited Display Area
US20110295649A1 (en) 2010-05-31 2011-12-01 International Business Machines Corporation Automatic churn prediction
US8756224B2 (en) 2010-06-16 2014-06-17 Rallyverse, Inc. Methods, systems, and media for content ranking using real-time data
US8380719B2 (en) 2010-06-18 2013-02-19 Microsoft Corporation Semantic content searching
US8364642B1 (en) 2010-07-07 2013-01-29 Palantir Technologies, Inc. Managing disconnected investigations
US8407341B2 (en) 2010-07-09 2013-03-26 Bank Of America Corporation Monitoring communications
US8554653B2 (en) * 2010-07-22 2013-10-08 Visa International Service Association Systems and methods to identify payment accounts having business spending activities
US8775530B2 (en) 2010-08-25 2014-07-08 International Business Machines Corporation Communication management method and system
US20120066166A1 (en) 2010-09-10 2012-03-15 International Business Machines Corporation Predictive Analytics for Semi-Structured Case Oriented Processes
US20120078595A1 (en) 2010-09-24 2012-03-29 Nokia Corporation Method and apparatus for ontology matching
US8549004B2 (en) 2010-09-30 2013-10-01 Hewlett-Packard Development Company, L.P. Estimation of unique database values
US8498998B2 (en) 2010-10-11 2013-07-30 International Business Machines Corporation Grouping identity records to generate candidate lists to use in an entity and relationship resolution process
WO2012054868A2 (en) 2010-10-21 2012-04-26 Visa International Service Association Software and methods for risk and fraud mitigation
WO2012061162A1 (en) 2010-10-25 2012-05-10 Intelius Inc. Cost-sensitive alternating decision trees for record linkage
JP5706137B2 (en) 2010-11-22 2015-04-22 インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Machines Corporation Method and computer program for displaying on a computer screen in real time along a plurality of posts (group of data) to a plurality of axes
CA2914169C (en) 2010-11-24 2018-01-23 Logrhythm, Inc. Scalable analytical processing of structured data
CN102546446A (en) 2010-12-13 2012-07-04 太仓市浏河镇亿网行网络技术服务部 Email device
US9141405B2 (en) 2010-12-15 2015-09-22 International Business Machines Corporation User interface construction
US8719166B2 (en) 2010-12-16 2014-05-06 Verizon Patent And Licensing Inc. Iterative processing of transaction information to detect fraud
US20120197660A1 (en) 2011-01-31 2012-08-02 Ez Derm, Llc Systems and methods to faciliate medical services
US20120197657A1 (en) 2011-01-31 2012-08-02 Ez Derm, Llc Systems and methods to facilitate medical services
IL211163D0 (en) 2011-02-10 2011-04-28 Univ Ben Gurion A method for generating a randomized data structure for representing sets, based on bloom filters
EP2678774A4 (en) 2011-02-24 2015-04-08 Lexisnexis Division Of Reed Elsevier Inc Methods for electronic document searching and graphically representing electronic document searches
WO2012119008A2 (en) 2011-03-01 2012-09-07 Early Warning Services, Llc System and method for suspect entity detection and mitigation
CA2830797A1 (en) 2011-03-23 2012-09-27 Detica Patent Limited An automated fraud detection method and system
US20120278249A1 (en) 2011-04-29 2012-11-01 American Express Travel Related Services Company, Inc. Generating an Identity Theft Score
US8861861B2 (en) * 2011-05-10 2014-10-14 Expensify, Inc. System and method for processing receipts and other records of users
US9104765B2 (en) 2011-06-17 2015-08-11 Robert Osann, Jr. Automatic webpage characterization and search results annotation
US8533165B2 (en) 2011-07-03 2013-09-10 Microsoft Corporation Conflict resolution via metadata examination
US8726379B1 (en) 2011-07-15 2014-05-13 Norse Corporation Systems and methods for dynamic protection from electronic attacks
US8982130B2 (en) 2011-07-15 2015-03-17 Green Charge Networks Cluster mapping to highlight areas of electrical congestion
US9996807B2 (en) 2011-08-17 2018-06-12 Roundhouse One Llc Multidimensional digital platform for building integration and analysis
US8732574B2 (en) 2011-08-25 2014-05-20 Palantir Technologies, Inc. System and method for parameterizing documents for automatic workflow generation
US8630892B2 (en) 2011-08-31 2014-01-14 Accenture Global Services Limited Churn analysis system
US8949164B1 (en) 2011-09-08 2015-02-03 George O. Mohler Event forecasting system
US20130226318A1 (en) 2011-09-22 2013-08-29 Dariusz Procyk Process transformation and transitioning apparatuses, methods and systems
BR112014008351A2 (en) 2011-10-05 2017-04-18 Mastercard International Inc mechanism nomination
US8849776B2 (en) 2011-10-17 2014-09-30 Yahoo! Inc. Method and system for resolving data inconsistency
US8626545B2 (en) 2011-10-17 2014-01-07 CrowdFlower, Inc. Predicting future performance of multiple workers on crowdsourcing tasks and selecting repeated crowdsourcing workers
US8843421B2 (en) 2011-11-01 2014-09-23 Accenture Global Services Limited Identification of entities likely to engage in a behavior
US20130124193A1 (en) 2011-11-15 2013-05-16 Business Objects Software Limited System and Method Implementing a Text Analysis Service
US9159024B2 (en) * 2011-12-07 2015-10-13 Wal-Mart Stores, Inc. Real-time predictive intelligence platform
CN103167093A (en) 2011-12-08 2013-06-19 青岛海信移动通信技术股份有限公司 Filling method of mobile phone email address
US8880420B2 (en) 2011-12-27 2014-11-04 Grubhub, Inc. Utility for creating heatmaps for the study of competitive advantage in the restaurant marketplace
US8843431B2 (en) 2012-01-16 2014-09-23 International Business Machines Corporation Social network analysis for churn prediction
US8909648B2 (en) 2012-01-18 2014-12-09 Technion Research & Development Foundation Limited Methods and systems of supervised learning of semantic relatedness
US9279898B2 (en) 2012-02-09 2016-03-08 Pgs Geophysical As Methods and systems for correction of streamer-depth bias in marine seismic surveys
US20130226944A1 (en) 2012-02-24 2013-08-29 Microsoft Corporation Format independent data transformation
GB2508573A (en) 2012-02-28 2014-06-11 Qatar Foundation A computer-implemented method and computer program for detecting a set of inconsistent data records in a database including multiple records
US8620963B2 (en) 2012-03-08 2013-12-31 eBizprise Inc. Large-scale data processing system, method, and non-transitory tangible machine-readable medium thereof
JP2013191187A (en) 2012-03-15 2013-09-26 Fujitsu Ltd Processing device, program and processing system
US20130262328A1 (en) 2012-03-30 2013-10-03 CSRSI, Inc. System and method for automated data breach compliance
US20130263019A1 (en) 2012-03-30 2013-10-03 Maria G. Castellanos Analyzing social media
US9298856B2 (en) 2012-04-23 2016-03-29 Sap Se Interactive data exploration and visualization tool
US8798354B1 (en) * 2012-04-25 2014-08-05 Intuit Inc. Method and system for automatic correlation of check-based payments to customer accounts and/or invoices
US9043710B2 (en) 2012-04-26 2015-05-26 Sap Se Switch control in report generation
US10304036B2 (en) 2012-05-07 2019-05-28 Nasdaq, Inc. Social media profiling for one or more authors using one or more social media platforms
EP2662782A1 (en) 2012-05-10 2013-11-13 Siemens Aktiengesellschaft Method and system for storing data in a database
US8788471B2 (en) * 2012-05-30 2014-07-22 International Business Machines Corporation Matching transactions in multi-level records
US9032531B1 (en) 2012-06-28 2015-05-12 Middlegate, Inc. Identification breach detection
US10163158B2 (en) 2012-08-27 2018-12-25 Yuh-Shen Song Transactional monitoring system
US20140068487A1 (en) 2012-09-05 2014-03-06 Roche Diagnostics Operations, Inc. Computer Implemented Methods For Visualizing Correlations Between Blood Glucose Data And Events And Apparatuses Thereof
EP2901303A4 (en) * 2012-09-25 2016-06-01 Moneydesktop Inc Aggregation source routing
US20140095509A1 (en) 2012-10-02 2014-04-03 Banjo, Inc. Method of tagging content lacking geotags with a location
JP6423348B2 (en) 2012-10-08 2018-11-14 フィッシャー−ローズマウント システムズ,インコーポレイテッド Dynamically reusable class
US9104786B2 (en) 2012-10-12 2015-08-11 International Business Machines Corporation Iterative refinement of cohorts using visual exploration and data analytics
US8688573B1 (en) * 2012-10-16 2014-04-01 Intuit Inc. Method and system for identifying a merchant payee associated with a cash transaction
US8914886B2 (en) 2012-10-29 2014-12-16 Mcafee, Inc. Dynamic quarantining for malware detection
US9501761B2 (en) 2012-11-05 2016-11-22 Palantir Technologies, Inc. System and method for sharing investigation results
US20140136285A1 (en) 2012-11-15 2014-05-15 Homer Tlc, Inc. System and method for classifying relevant competitors
US20140143009A1 (en) 2012-11-16 2014-05-22 International Business Machines Corporation Risk reward estimation for company-country pairs
US20140157172A1 (en) 2012-11-30 2014-06-05 Drillmap Geographic layout of petroleum drilling data and methods for processing data
US20140156527A1 (en) 2012-11-30 2014-06-05 Bank Of America Corporation Pre-payment authorization categorization
US20150073954A1 (en) 2012-12-06 2015-03-12 Jpmorgan Chase Bank, N.A. System and Method for Data Analytics
US9497289B2 (en) 2012-12-07 2016-11-15 Genesys Telecommunications Laboratories, Inc. System and method for social message classification based on influence
US9294576B2 (en) 2013-01-02 2016-03-22 Microsoft Technology Licensing, Llc Social media impact assessment
US20140195515A1 (en) 2013-01-10 2014-07-10 I3 Analytics Methods and systems for querying and displaying data using interactive three-dimensional representations
US8639552B1 (en) 2013-01-24 2014-01-28 Broadvision, Inc. Systems and methods for creating and sharing tasks
US9892026B2 (en) 2013-02-01 2018-02-13 Ab Initio Technology Llc Data records selection
US20140222793A1 (en) 2013-02-07 2014-08-07 Parlance Corporation System and Method for Automatically Importing, Refreshing, Maintaining, and Merging Contact Sets
US20140222521A1 (en) 2013-02-07 2014-08-07 Ibms, Llc Intelligent management and compliance verification in distributed work flow environments
US9264393B2 (en) 2013-02-13 2016-02-16 International Business Machines Corporation Mail server-based dynamic workflow management
US8744890B1 (en) 2013-02-14 2014-06-03 Aktana, Inc. System and method for managing system-level workflow strategy and individual workflow activity
US20140244284A1 (en) 2013-02-25 2014-08-28 Complete Consent, Llc Communication of medical claims
US9286618B2 (en) * 2013-03-08 2016-03-15 Mastercard International Incorporated Recognizing and combining redundant merchant designations in a transaction database
US10140664B2 (en) 2013-03-14 2018-11-27 Palantir Technologies Inc. Resolving similar entities from a transaction database
US8903717B2 (en) 2013-03-15 2014-12-02 Palantir Technologies Inc. Method and system for generating a parser and parsing complex data
GB2513720A (en) 2013-03-15 2014-11-05 Palantir Technologies Inc Computer-implemented systems and methods for comparing and associating objects
US8924388B2 (en) 2013-03-15 2014-12-30 Palantir Technologies Inc. Computer-implemented systems and methods for comparing and associating objects
US8855999B1 (en) 2013-03-15 2014-10-07 Palantir Technologies Inc. Method and system for generating a parser and parsing complex data
GB2513721A (en) 2013-03-15 2014-11-05 Palantir Technologies Inc Computer-implemented systems and methods for comparing and associating objects
US9372929B2 (en) 2013-03-20 2016-06-21 Securboration, Inc. Methods and systems for node and link identification
US20140358789A1 (en) 2013-05-30 2014-12-04 B. Scott Boding Acquirer facing fraud management system and method
US9576248B2 (en) 2013-06-01 2017-02-21 Adam M. Hurwitz Record linkage sharing using labeled comparison vectors and a machine learning domain classification trainer
US8601326B1 (en) 2013-07-05 2013-12-03 Palantir Technologies, Inc. Data quality monitors
GB2517582A (en) 2013-07-05 2015-02-25 Palantir Technologies Inc Data quality monitors
US8838538B1 (en) 2013-07-31 2014-09-16 Palantir Technologies, Inc. Techniques for replicating changes to access control lists on investigative analysis data
US9378030B2 (en) 2013-10-01 2016-06-28 Aetherpal, Inc. Method and apparatus for interactive mobile device guidance
US8938686B1 (en) 2013-10-03 2015-01-20 Palantir Technologies Inc. Systems and methods for analyzing performance of an entity
US8812960B1 (en) 2013-10-07 2014-08-19 Palantir Technologies Inc. Cohort-based presentation of user interaction data
US8832594B1 (en) 2013-11-04 2014-09-09 Palantir Technologies Inc. Space-optimized display of multi-column tables with selective text truncation based on a combined text width
US9356937B2 (en) 2013-11-13 2016-05-31 International Business Machines Corporation Disambiguating conflicting content filter rules
US20150134512A1 (en) 2013-11-13 2015-05-14 Mastercard International Incorporated System and method for detecting fraudulent network events
US20150161611A1 (en) 2013-12-10 2015-06-11 Sas Institute Inc. Systems and Methods for Self-Similarity Measure
US9105000B1 (en) 2013-12-10 2015-08-11 Palantir Technologies Inc. Aggregating data from a plurality of data sources
US20150188872A1 (en) 2013-12-26 2015-07-02 Palantir Technologies, Inc. System and method for detecting confidential information emails
US8832832B1 (en) 2014-01-03 2014-09-09 Palantir Technologies Inc. IP reputation
US9129219B1 (en) 2014-06-30 2015-09-08 Palantir Technologies, Inc. Crime risk forecasting
US9256664B2 (en) 2014-07-03 2016-02-09 Palantir Technologies Inc. System and method for news events detection and visualization
US9483546B2 (en) 2014-12-15 2016-11-01 Palantir Technologies Inc. System and method for associating related records to common entities across multiple lists

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110099133A1 (en) * 2009-10-28 2011-04-28 Industrial Technology Research Institute Systems and methods for capturing and managing collective social intelligence information
CN102054015A (en) * 2009-10-28 2011-05-11 财团法人工业技术研究院 System and method of organizing community intelligent information by using organic matter data model
US20130166480A1 (en) * 2011-12-21 2013-06-27 Telenav, Inc. Navigation system with point of interest classification mechanism and method of operation thereof

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10061828B2 (en) 2006-11-20 2018-08-28 Palantir Technologies, Inc. Cross-ontology multi-master replication
US9501552B2 (en) 2007-10-18 2016-11-22 Palantir Technologies, Inc. Resolving database entity information
US9846731B2 (en) 2007-10-18 2017-12-19 Palantir Technologies, Inc. Resolving database entity information
US9348499B2 (en) 2008-09-15 2016-05-24 Palantir Technologies, Inc. Sharing objects that rely on local resources with outside servers
US9880987B2 (en) 2011-08-25 2018-01-30 Palantir Technologies, Inc. System and method for parameterizing documents for automatic workflow generation
US9715518B2 (en) 2012-01-23 2017-07-25 Palantir Technologies, Inc. Cross-ACL multi-master replication
US9898335B1 (en) 2012-10-22 2018-02-20 Palantir Technologies Inc. System and method for batch evaluation programs
US10140664B2 (en) 2013-03-14 2018-11-27 Palantir Technologies Inc. Resolving similar entities from a transaction database
US10152531B2 (en) 2013-03-15 2018-12-11 Palantir Technologies Inc. Computer-implemented systems and methods for comparing and associating objects
US9495353B2 (en) 2013-03-15 2016-11-15 Palantir Technologies Inc. Method and system for generating a parser and parsing complex data
US9286373B2 (en) 2013-03-15 2016-03-15 Palantir Technologies Inc. Computer-implemented systems and methods for comparing and associating objects
US10120857B2 (en) 2013-03-15 2018-11-06 Palantir Technologies Inc. Method and system for generating a parser and parsing complex data
US9996229B2 (en) 2013-10-03 2018-06-12 Palantir Technologies Inc. Systems and methods for analyzing performance of an entity
US10198515B1 (en) 2013-12-10 2019-02-05 Palantir Technologies Inc. System and method for aggregating data from a plurality of data sources
US10180977B2 (en) 2014-03-18 2019-01-15 Palantir Technologies Inc. Determining and extracting changed data from a data source
US9483546B2 (en) 2014-12-15 2016-11-01 Palantir Technologies Inc. System and method for associating related records to common entities across multiple lists
US10242072B2 (en) 2014-12-15 2019-03-26 Palantir Technologies Inc. System and method for associating related records to common entities across multiple lists
US10103953B1 (en) 2015-05-12 2018-10-16 Palantir Technologies Inc. Methods and systems for analyzing entity performance
US10146853B2 (en) 2015-05-15 2018-12-04 International Business Machines Corporation Determining entity relationship when entities contain other entities
US9392008B1 (en) 2015-07-23 2016-07-12 Palantir Technologies Inc. Systems and methods for identifying information related to payment card breaches
US9661012B2 (en) 2015-07-23 2017-05-23 Palantir Technologies Inc. Systems and methods for identifying information related to payment card breaches
US10127289B2 (en) 2015-08-19 2018-11-13 Palantir Technologies Inc. Systems and methods for automatic clustering and canonical designation of related data in various data structures
US9984428B2 (en) 2015-09-04 2018-05-29 Palantir Technologies Inc. Systems and methods for structuring data from unstructured electronic data files
US9514414B1 (en) 2015-12-11 2016-12-06 Palantir Technologies Inc. Systems and methods for identifying and categorizing electronic documents through machine learning
US9760556B1 (en) 2015-12-11 2017-09-12 Palantir Technologies Inc. Systems and methods for annotating and linking electronic documents
US10133588B1 (en) 2016-10-20 2018-11-20 Palantir Technologies Inc. Transforming instructions for collaborative updates
US10235533B1 (en) 2017-12-01 2019-03-19 Palantir Technologies Inc. Multi-user access controls in electronic simultaneously editable document editor

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